max_us = g.second;
    }
  }
  int max_digits = 1;
  while (max_us >= 10.0) {
    max_us /= 10.0;
    ++max_digits;
  }
  // Dump stats out.
  printf("Benchmark ran %zu iterations over %lld us\n", count_us,
         static_cast<long long>(stats.total_us));  // NOLINT
  for (const auto& g : groups) {
    printf("  %-*s %*.3f us\n", max_label_size, g.first.c_str(), max_digits + 4,
           g.second);

	VMOV V4.B16, V20.B16
	VMOV V5.B16, V21.B16
	VMOV V6.B16, V22.B16
	VMOV V7.B16, V23.B16
	VMOV V8.B16, V24.B16
	VMOV V9.B16, V25.B16
	VMOV V10.B16, V26.B16
	VMOV V11.B16, V27.B16

	// 4 iterations. Each iteration is 8 quarter-rounds.
	MOVD $4, R0
loop:
	QR(V0, V4, V8, V12)
	QR(V1, V5, V9, V13)
	QR(V2, V6, V10, V14)
	QR(V3, V7, V11, V15)

	QR(V0, V5, V10, V15)
	QR(V1, V6, V11, V12)
	QR(V2, V7, V8, V13)

	g1(m)
	g2(m)
	g3(m)
	g4(m)
	g5(m)
}

// Worst-case scenario.
// There are 10 unknown type parameters. In each iteration of
// constraint type inference we infer one more, from right to left.
// Each iteration looks repeatedly at all 11 type parameters,
// requiring a total of 10*11 = 110 iterations with the current
// implementation. Pathological case.

  public static <S> ElementOrder<S> unordered() {
    return new ElementOrder<>(Type.UNORDERED, null);
  }

  /**
   * Returns an instance which specifies that ordering is guaranteed to be always be the same across
   * iterations, and across releases. Some methods may have stronger guarantees.
   *
   * <p>This instance is only useful in combination with {@code incidentEdgeOrder}, e.g. {@code
   * graphBuilder.incidentEdgeOrder(ElementOrder.stable())}.

  public static <S> ElementOrder<S> unordered() {
    return new ElementOrder<>(Type.UNORDERED, null);
  }

  /**
   * Returns an instance which specifies that ordering is guaranteed to be always be the same across
   * iterations, and across releases. Some methods may have stronger guarantees.
   *
   * <p>This instance is only useful in combination with {@code incidentEdgeOrder}, e.g. {@code
   * graphBuilder.incidentEdgeOrder(ElementOrder.stable())}.

	// Len
	n := r.Len()
	if n != N {
		t.Errorf("r.Len() == %d; expected %d", n, N)
	}

	// iteration
	n = 0
	s := 0
	r.Do(func(p any) {
		n++
		if p != nil {
			s += p.(int)
		}
	})
	if n != N {
		t.Errorf("number of forward iterations == %d; expected %d", n, N)
	}
	if sum >= 0 && s != sum {
		t.Errorf("forward ring sum = %d; expected %d", s, sum)
	}

	if r == nil {

package main

import (
	"fmt"
	"math"
	"time"
)

// checkLinear asserts that the running time of f(n) is in O(n).
// tries is the initial number of iterations.
func checkLinear(typ string, tries int, f func(n int)) {
	// Depending on the machine and OS, this test might be too fast
	// to measure with accurate enough granularity. On failure,

	ssc.enqueueStatefulSet(set)
	fakeWorker(ssc)
	selector, err := metav1.LabelSelectorAsSelector(set.Spec.Selector)
	if err != nil {
		return err
	}
	iterations := 0
	for (maxIterations < 0 || iterations < maxIterations) && set.Status.ReadyReplicas < *set.Spec.Replicas {
		iterations++
		pods, err := om.podsLister.Pods(set.Namespace).List(selector)
		if err != nil {
			return err
		}
		ord := len(pods) - 1

  OpPassManager pass_manager;
  llvm::StringRef device_type = "XLA_CPU_JIT";
  absl::string_view kInlinePass =
      "inline{default-pipeline=canonicalize "
      "inlining-threshold=4294967295 max-iterations=4 }";

  CreateConvertMlirToXlaHloPipeline(pass_manager, device_type,
                                    /*enable_op_fallback=*/true,
                                    /*custom_legalization_passes*/ {});

  }
};

// Test for resource leaks related to TensorFlow session closing requirements
// when loading and unloading large numbers of SavedModelBundles.
// TODO(sukritiramesh): Increase run iterations and move outside of the test
// suite.
TEST_F(LoaderTest, ResourceLeakTest) {
  SavedModelBundleLite bundle;
  SessionOptions session_options;
  RunOptions run_options;

  const string export_dir =